On-time delivery doesn’t happen on it’s own; rather, it’s the result of considerable planning, production, and accounting in the manufacturing process. As well, improved service levels means more repetitive business coming from continuously satisfied customers. In other words, predictability and repeatability allow manufacturers to more accurately forecast the economic, material, manpower, and production yields that make a company grow strong and regarded well by others in the supply-chain and the marketplace.

Planning, production, and accounting in the manufacturing process are intentional, and their validity and repeatability are paramount for prosperous growth. To the degree that these variables can be controlled, a robust enterprise resource planning (ERP) software system should be well-suited to managing such material and production variability as well accounting for raw materials and finished goods in the manufacturing process. ERP is the application in discrete manufacturing that helps make production jobs highly predictable and repeatable.

The primary reason for this is that discrete manufacturing, especially in sub-assembly and continuous assembly production, often has a (more…)

It is axiomatic that all enterprise resource planning (ERP) systems are not created equal. Some are quite industry specific, while others might be application specific. Some might have very narrow capabilities, while others might be designed for generic purposes across a broad array of industries—everything from thermoform plastic pressing to the greens-keeping of sporting facilities. Furthermore, with decades of maturity behind the concept, ERP has moved beyond just being a means to facilitate discrete manufacturing, but now is used to optimize process manufacturing and various hybrid systems that blend discrete with process.

Therefore, questions invariably arise when trying to determine the ERP system best suited for the type of manufacturing operation that needs it. Normally, the functional capabilities of a discrete-oriented ERP application are inherently different than those of either a generic or process-oriented ERP application. Knowing the differences in the two can often make the difference between positive returns on the software system investment and the creation of significant risk and taxing overhead costs because of it. For example, do you know the (more…)

In the first part of our two-part series on improved pricing models for manufacturers, we introduced the notion that pricing is an area where shrinking margins can be countered. Insofar as traditional qualitative methods for pricing are unable (or unwilling) to control for supply-chain and customer variables, as well as automation, most approaches end up being manual and/or ad hoc. Simply put: These approaches have minimal chances of producing maximum margins.

To achieve a more precise pricing scheme, manufacturers must employ quantitative pricing methods that overcome the challenges found in modern production. Doing so means making pricing decisions based on business intelligence—not business guesswork. The process of quantitative pricing begins by first recognizing what is working and not working with regards to methodologies, then deciding to take the pricing task to a more formal level that is informed by a variety of data.

First, it is vital to realize that ad hoc pricing facilitates price differentiation; that is, diversified manufacturers typically have extensive product portfolios and very sizable customer bases, and therefore (more…)

With increasingly unpredictable costs for raw materials, energy, and even capital acquisition, manufacturing today is a volatile, roller coaster ride filled with peaks and valleys. Manufacturers face a vast array of complex challenges including intense competition, increasing costs, and accelerated product life cycles. It is true that to, some extent, technology investments in enterprise systems such as ERP, MRP, and CRM have helped to control operating costs and increase corporate agility.

However, as adoption of these capabilities has spread to the point of producing something akin to a parity of efficiency in manufacturing, they can dilute gains in competitive advantage. What is important to realize is that the resulting quantity and quality of data produced by ERP systems have set the stage for business intelligence applications that leverage such data to analyze and optimize business performance in areas other than the shop floor.

For example, consider what competitive advantages can be built around the notion of pricing. Using data to derive customer segmentation and optimization models can recommend prices that are much more profitable than those currently in market. This is a pricing science that can be easily (more…)